Revenue versus covers

In the dynamic environment of hotel food & beverage (F&B) divisions, accurately measuring productivity is crucial for operational efficiency and profitability. Two common metrics used are revenue per labor hour (RevPOLU) and covers per labor hour. At d2o, we believe that revenue per labor hour is often a more reliable measure of productivity compared to covers per labor hour, considering the advantages and limitations of each.

What defines a cover?

In a restaurant setting, a cover typically refers to a single diner. However, the definition can vary widely between establishments. Some might count a cover as anyone served, regardless of whether they only have a drink, starter, full meal, or even share a meal, while others might define a cover as a single transaction, where one person may pay for many guests. This inconsistency in defining what constitutes a cover can lead to ambiguities and challenges in using covers as a reliable activity and cost driver or productivity measurement.

Should covers be included in a PMI project scope?

When PMI is implemented for clients with F&B operations, a preference to work solely with covers is often encountered. Clients may not fully understand our recommendation to measure an F&B outlet’s productivity using revenue rather than covers.

The following reports need to be analyzed before deciding to include covers in the project’s scope:

1. Definition and routines: Inspect the standard operating procedure to understand the organization’s definition of covers and their routines for posting covers in their point of sale (POS) system.

2. Actuals: Review a POS report on covers for the past few months to determine if the organization consistently records covers in a meaningful way to assess productivity.

3. Reservations: If the organization utilizes a reservation system, examine an on the books report for covers to understand if integration would be useful.

Note: When integrating with an F&B reservation system to obtain OTB data, there must be covers history and actuals imported daily from the POS system for it to be beneficial in PMI.

Based on the analysis of these reports, discuss the general and specific pros and cons of using covers in PMI.

Implementation preferences

As a rule, d2o recommends that revenue per labor hour is prioritized as a productivity measurement and that covers are used only as an additional guideline alongside revenue. It is never recommended to work with covers alone.

If the purpose for choosing revenue above covers is still unclear, the following sections may help to bring clarity.

Revenue per labor hour: The preferred metric

Revenue per labor hour is a straightforward metric calculated by taking the total revenue generated divided by the number of labor hours worked. This measure offers several benefits:

1. Accurate financial performance: Revenue per labor hour directly reflects the financial performance of an outlet, showing how effectively staff are serving and upselling in relation to how much customers are spending. The downside, however, is that it does not always correlate perfectly with the effort required by the waitstaff.

• • • • For example, revenue per labor hour may be a difficult metric to use in situations where menu items are heavily discounted or corporate in-house dinners and events might not generate significant, if any, revenue, but they still require the same level of staffing. Therefore, using covers as supplementary information is advisable to get a complete picture of staff requirements and workload.

2. Assured quality and accurate data: Revenue figures are recorded through the POS system and are subject to reconciliation and even audit, ensuring accuracy and minimizing the risk of mistakes and manipulation.

3. Sales performance indicator: This metric highlights the effectiveness of sales strategies and how proficient the waitstaff are at generating income.

4. Consistency: Revenue is a consistent measurement not subject to ambiguities or inconsistent definitions.

One perceived challenge with using revenue per labor hour is that it can initially be difficult for department heads to schedule waiters and other restaurant staff based on revenue, especially if they are accustomed to working with covers. To make this transition smoother, department heads should follow the solution presented in each outlet’s cockpit:

1. Productivity target: Be familiar with the monthly productivity target set by the general manager and head office. This target may be something like €80 per labor hour.

2. Daily revenue forecast: Monitor the daily revenue forecast for this outlet generated by the Live forecast.

3. Required labor hours: For each day, PMI divides the live and fluctuating forecasted revenue for the outlet by the set productivity target (RevPOLU) to calculate the labor hours needed to meet the activity level. This is known as the SMART forecast, which department heads should follow when scheduling in their TKS.

• • • • For example, if the forecasted revenue for a day is €3,000 and the set productivity target is €80 per labor hour, the outlet needs 38 labor hours for that day (€3,000 / €80 = 37.5, rounded to 38).

4. Flexible implementation: Spread the SMART forecast generated labor hours across shifts in the TKS to match the activity level throughout the day. This allows for flexible implementation by the heads of department.

Note: The above examples explain the standard calculation for SMART when there is a primary cost driver selected. 

Covers per labor hour: Limitations and drawbacks

Covers per labor hour calculates the number of customers served divided by the number of labor hours worked. While covers can provide a good basic measure of customer volume, it has some drawbacks.

1. Unclear definition: Covers can be difficult to define consistently. Is a cover counted as a drink, a starter, or a full meal? How do you handle diners sharing a meal? These inconsistencies can lead to misleading data. If a hotel’s definition of a cover is very clear and consistently applied, covers may be useful as an additional guiding measure, as explained above.

2. Data mistakes and manipulation: Waitstaff can easily misreport covers, either intentionally or unintentionally. For example, reopening tabs or double-counting customers can inflate cover counts, making the data unreliable.

3. Lack of financial insight: Covers do not provide insight into revenue generation or the financial health of the outlet. High covers with low spending per customer can still result in poor financial performance.

4. Limited sales performance insight: This metric does not account for the effectiveness of upselling, or the average spent per customer, which are critical for maximizing revenue.

Conclusion

For F&B divisions in hotels, revenue per labor hour is a more reliable and insightful productivity measure compared to covers per labor hour. Revenue provides a clear, objective, and financially meaningful indicator of performance. It reflects how well waitstaff are selling and how much customers are spending, offering a true picture of the outlet’s success.

Covers are prone to inconsistencies and manipulation, making them less reliable for gauging productivity. If covers are clearly and consistently defined and applied, they can be a useful additional metric alongside revenue. By focusing on revenue per labor hour, managers can better understand their financial performance, make informed decisions, and drive profitability in their F&B operations.